Engineering Manager, Machine Learning Operations
Tasks
- Adopt ML best practices
- Apply agile and lean fast flow principles
- Bridge product needs to execution
- Build execution plans for initiatives
- Coordinate geographically distributed teams
- Define MLOps roadmaps
- Deliver mlops roadmap items on time
- Describe technical content for multiple audiences
- Drive ML experimentation and innovation
- Ensure high quality of deliverables
- Ensure reliability and efficiency of scalable solutions
- Establish psychological safety culture
- Lead MLOps team direction
- Model company values and desired behaviors
- Remove roadblocks and improve processes
- Set KPIs and success criteria
Perks/Benefits
- 401k match
- Annual educational stipend
- Comprehensive health benefits
- Employee stock program
- Paid family and paternity leave
- Paid sabbatical
- Transportation stipend
- Tuition reimbursement
Skills/Tech-stack
AWS | Agile | Amazon SageMaker | Apache Airflow | Apache Kafka | CI/CD | Cloud Native | Cloud platform | Containerization | Docker | Elasticsearch | FastAPI | GitOps | Google Cloud | Google Cloud Platform | Google Vertex | Google Vertex AI | Grafana | Kubeflow | Kubernetes | Langchain | Lean | Learning operations | MLflow | Machine Learning | Machine Learning Operations | Maintenance | Monitoring | NoSQL | Prometheus | PyTorch | Python | Redis | SQL | Scikit-learn | TensorFlow | Vertex AI | Weights and Biases
Education
Regions
Countries
States
Cities
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